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Object Recognition

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하위 태스크: 3
평가표: 9
보존된 평가 기록: 31

Object recognition is a computer vision technique for detecting + classifying objects in images or videos. Since this is a combined task of object detection plus image classification, the state-of-the-art tables are recorded for each component task here and here.

<span style="color:grey; opacity: 0.6">( Image credit: Tensorflow Object Detection API )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/neouyghur/sess

공식 코드

SESS: Saliency Enhancing with Scaling and Sliding

https://github.com/netflix/clove

공식 코드

CLoVe: Encoding Compositional Language in Contrastive Vision-Language Models

https://github.com/neuroailab/VIE

공식 코드

Unsupervised Learning from Video with Deep Neural Embeddings

https://github.com/neuroailab/tnn

공식 코드

Task-Driven Convolutional Recurrent Models of the Visual System

https://github.com/nineRishav/Lost-In-Context

공식 코드

Lost in Context: The Influence of Context on Feature Attribution Methods for Object Recognition

https://github.com/niranjanrajesh02/dcv_src

공식 코드

Developmental Pretraining (DPT) for Image Classification Networks

https://github.com/notacracker/cotr

공식 코드

COTR: Compact Occupancy TRansformer for Vision-based 3D Occupancy Prediction

https://github.com/numenta/htmpapers/tree/master/bmvc/grid_cell_path_integration_for_movement_based_visual_object_recognition

공식 코드

Grid Cell Path Integration For Movement-Based Visual Object Recognition

https://github.com/open-mmlab/mmdetection/tree/3.x/configs/rtmdet

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RTMDet: An Empirical Study of Designing Real-Time Object Detectors

https://github.com/open-mmlab/mmdetection/tree/master/mmdet/models/necks

공식 코드

Feature Pyramid Grids

https://github.com/open-mmlab/mmtracking

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Temporal RoI Align for Video Object Recognition

https://github.com/openai/CLIP

공식 코드

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/pedro-morgado/nettailor

공식 코드

NetTailor: Tuning the Architecture, Not Just the Weights

https://github.com/phoenixz810/mg-llava

공식 코드

MG-LLaVA: Towards Multi-Granularity Visual Instruction Tuning

https://github.com/plai-group/simple-cnaps

공식 코드

Improved Few-Shot Visual Classification

https://github.com/ppengtang/oicr

공식 코드

Multiple Instance Detection Network with Online Instance Classifier Refinement

https://github.com/pramodv1993/VAST

공식 코드

Visual Probing and Correction of Object Recognition Models with Interactive user feedback

https://github.com/princetonvisualai/imagenet-face-obfuscation

공식 코드

A Study of Face Obfuscation in ImageNet

https://github.com/prithv1/pasta

공식 코드

PASTA: Proportional Amplitude Spectrum Training Augmentation for Syn-to-Real Domain Generalization

https://github.com/pulp-platform/stream-ebpc

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EBPC: Extended Bit-Plane Compression for Deep Neural Network Inference and Training Accelerators

https://github.com/qiujumin/don-rl

공식 코드

Decision-making and control with diffractive optical networks

https://github.com/rachtsy/momentumsmoe

공식 코드

MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts

https://github.com/rahulsmehta/sparsity-experiments

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Sparse Transfer Learning via Winning Lottery Tickets

https://github.com/rakshith-2905/sista

공식 코드

Target-Aware Generative Augmentations for Single-Shot Adaptation

https://github.com/raphaelmemmesheimer/sl-dml

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SL-DML: Signal Level Deep Metric Learning for Multimodal One-Shot Action Recognition

https://github.com/rdz98/unsup-vvs

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Improving Unsupervised Task-driven Models of Ventral Visual Stream via Relative Position Predictivity

https://github.com/rehg-lab/dope_selfsup

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Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization

https://github.com/renll/RSAM

공식 코드

Recurrent Soft Attention Model for Common Object Recognition

https://github.com/rfeinman/SK-regularization

공식 코드

Learning a smooth kernel regularizer for convolutional neural networks

https://github.com/rfeinman/learning-to-learn

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Learning Inductive Biases with Simple Neural Networks

https://github.com/rgeirhos/Stylized-ImageNet

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ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

https://github.com/rgeirhos/generalisation-humans-DNNs

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Generalisation in humans and deep neural networks

https://github.com/rgeirhos/object-recognition

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Comparing deep neural networks against humans: object recognition when the signal gets weaker

https://github.com/rgerum/spectral-representations

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Different Spectral Representations in Optimized Artificial Neural Networks and Brains

https://github.com/ricky-ma/ODDObjects

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ODDObjects: A Framework for Multiclass Unsupervised Anomaly Detection on Masked Objects

https://github.com/rkwitt/GuidedAugmentation

공식 코드

AGA: Attribute Guided Augmentation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.